Local regression smoothers with set-valued outcome data

This paper proposes a method to conduct local linear regression smoothing in the presence of set-valued outcome data. The proposed estimator is shown be consistent, and its mean squared error asymptotic distribution are derived. A build tubes around provided, small Monte Carlo exercise conducted confirm good finite sample properties estimator. usefulness illustrated on novel dataset from clinical trial assess effect certain genes' expressions different lung cancer treatments outcomes.